Severe Coagulation Dysfunction caused by Vitamin K Deficiency in an Elderly Patient.

BACKGROUND: Vitamin K deficiency can lead to severe coagulation dysfunction, which may be dangerous and fatal, especially in patients undergoing surgery. METHODS: We report an 84-year-old male patient with gallstones and cholecystitis who had a severe coagulation disorder without bleeding symptoms after endoscopic papillary balloon dilation for removal of bile duct stones. After vitamin K supplementation, the coagulation dysfunction was corrected the next day. RESULTS: In this case, long-term antibiotic treatment, inadequate diet, and abnormal liver function led to coagulation dysfunction. After vitamin K supplementation, the blood coagulation disorder was corrected and serious consequences were prevented. Significantly elevated coagulation function was considered to be caused by vitamin K deficiency. CONCLUSIONS: This case indicates that coagulation dysfunction caused by vitamin K deficiency may occur within a few days. Laboratory personnel should fully understand the risks of vitamin K deficiency in elderly patients undergoing surgery with severely restricted diet, impaired absorption, and long-term use of cephalosporin anti-inflammatory therapy, and promptly remind clinical doctors.

Direct electrochemical detection of Cu(â ¡) ions in juice and tea beverage samples using MWCNTs-BMIMPF6-Nafion modified GCE electrodes.

Due to a small amount of Cu (Ⅱ) ions being beneficial and too much being harmful, it is necessary to establish a rapid and direct detection method. Herein, we reported a platform based on multiwalled carbon nanotubes (MWCNTs), 1-butyl-3-methylimidazolium hexafluorophosphate (BMIMPF6), and Nafion solution-modified glassy carbon electrode (GCE) for the direct electrochemical detection of Cu (II) ions. We used differential pulse anodic stripping voltammetry, including the electrodeposition of Cu (Ⅱ) ions on the modified GCE and subsequent anodic stripping. Under the optimum conditions, the linear range was 20 µg·L-1 âˆ¼ 950 µg·L-1, the limit of detection (LOD) was 16 µg·L-1, and the limit of quantification (LOQ) was 54 µg·L-1 for Cu (II). We realized the quantitative detection of Cu (Ⅱ) ions in juice and tea beverage without tedious pretreatment. The result showed that the sensor had good anti-interference and practicability for actual food samples.

ZnCdSe-CdTe quantum dots: A "turn-off" fluorescent probe for the detection of multiple adulterants in an herbal honey.

To enhance the power of untargeted detection, a "turn-off" fluorescent probe with double quantum dots (QDs) was developed and coupled with chemometrics for rapid detection of multiple adulterants in an herbal (Rhus chinensis Mill., RCM) honey. The double water-soluble ZnCdSe-CdTe QDs have two separate and strong fluorescent peaks, which can be quenched by honey and extraneous adulterants with varying degrees. Class models of pure RCM honey samples collected from 6 different producing areas (n = 122) were developed using one-class partial least squares (OCPLS). Four extraneous adulterants, including glucose syrup, sucrose syrup, fructose syrup, and glucose-fructose syrup were added to pure honey samples at the levels of 0.5% to 10% (w/w). As a result, the OCPLS model using the second-order derivative (D2) spectra could detect 1.0% (w/w) of different syrups in RCM honey, with a sensitivity of 0.949. The double water-soluble QDs, which can be adjusted for analysis of other water-soluble food samples, has largely extended the capability of traditional fluorescence and will provide a potentially more sensitive and specific analysis method for food frauds.

Fusion of near-infrared and fluorescence spectroscopy for untargeted fraud detection of Chinese tea seed oil using chemometric methods.

BACKGROUND: This paper investigated the feasibility of data fusion of near-infrared (NIR) and fluorescence spectroscopy for rapid analysis of cheap vegetable oils in Chinese Camellia oleifera Abel. (COA) oil. Because practical frauds usually involve adulterations of multiple known and unknown cheap oils, traditional analytical methods aimed at detecting one or more known adulterants are insufficient to identify adulterated COA oil. Therefore, untargeted analysis was performed by developing class models of pure COA oil using robust one-class partial least squares (OCPLS). RESULTS: The most accurate OCPLS model was obtained with fusion of standard normal variate (SNV)-NIR and SNV-fluorescence spectra with sensitivity of 0.954 and specificity of 0.91. Robust OCPLS could detect adulterations with 2% (w/w) or more cheap oils, including rapeseed oil, sunflower seed oil, corn oil and peanut oil. CONCLUSION: Fusion of NIR and fluorescence data and chemometrics provided enhanced capacity for rapid and untargeted analysis of multiple adulterations in Chinese COA oils. © 2018 Society of Chemical Industry.